Good Volatility, Bad Volatility, and Option Pricing

Bruno Feunou and Cédric Okou

Journal of Financial and Quantitative Analysis, 2019, vol. 54, issue 2, 695-727

Abstract: Advances in variance analysis permit the splitting of the total quadratic variation of a jump-diffusion process into upside and downside components. Recent studies establish that this decomposition enhances volatility predictions and highlight the upside/downside variance spread as a driver of the asymmetry in stock price distributions. To appraise the economic gain of this decomposition, we design a new and flexible option pricing model in which the underlying asset price exhibits distinct upside and downside semivariance dynamics driven by the model-free proxies of the variances. The new model outperforms common benchmarks, especially the alternative that splits the quadratic variation into diffusive and jump components.

Date: 2019
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Working Paper: Good Volatility, Bad Volatility and Option Pricing (2017)
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